Cooperative Agreement W911NF2520167

This National Science Foundation (NSF) SBIR Phase I Project Grant award of $305,000 to Beesafe Labs, LLC will develop defensive AI technology to help reduce the economic and emotional harm caused by social engineering cyber-attacks. The project aims to create an automated, scalable system capable of intercepting, tracing, and aggregating data on social engineering attacks in real-time. This intelligence-gathering capability will provide valuable data to the cybersecurity industry, government,...

This Project Grant from the National Science Foundation's Technology, Innovation, and Partnerships program totaling $100,000.00 was awarded on June 15, 2022 to Texas Tech University to develop a technology platform to automatically measure user susceptibility to social engineering attacks. The platform will quantify individual users' personality traits, demographics, education, and experiences using publicly available information to estimate susceptibility to phishing attacks. This will help...

This $265,948 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to improve the reliability and scientific integrity of threat modeling experiments in software security. The project aims to develop best practices for conducting human-centered threat modeling studies, which are essential for ensuring software is secure. Key research activities include qualitative investigations of current...

The Research Foundation For The State University Of New York (RF SUNY), also known as Stony Brook University, received a $399,767 Project Grant award from the National Science Foundation Division of Computer and Network Systems on October 1, 2021 to support research titled "COLLABORATIVE RESEARCH: SATC: CORE: MEDIUM: DEFENDING AGAINST SOCIAL ENGINEERING ATTACKS WITH IN-BROWSER AI." The grant supports research and development of in-browser artificial intelligence techniques to defend...

The University of Georgia Research Foundation, Inc. was awarded a $399,999 Project Grant from the National Science Foundation Division of Computer and Network Systems. The grant supports the collaborative research project "DEFENDING AGAINST SOCIAL ENGINEERING ATTACKS WITH IN-BROWSER AI" under the Computer and Information Science and Engineering program (CFDA #47.070). The research aims to develop in-browser artificial intelligence techniques to defend against social engineering...

This Project Grant award from the National Science Foundation (NSF) Division of Behavioral and Cognitive Sciences, under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), provides $200,000 to San Jose State University Research Foundation to investigate conversational social engineering attacks, known as "vishing", and develop software to detect these attacks in real-time. The key products and services to be delivered under this 4-year award include: Creating two data...

This $100,000 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports the development of an empathy-based framework to enhance privacy education and design. The project team at the University of Notre Dame is using generative AI to create synthetic personas with AI-generated personal data. These personas are then used to design interactive sandboxes and developer tools that allow individuals to empathize with the...

The National Science Foundation awarded a $300,000 Project Grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Central Florida Board of Trustees to develop an "SATC 2.0: EDU: EXPERIENTIAL LEARNING OF DARK PATTERNS FOR CYBERSECURITY AND PRIVACY" platform. The goal of this 3-year project is to create a learning platform that educates older adults and those with limited digital literacy about "dark patterns" - user interface...

The National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program has awarded the University of California, San Diego (UCSD) a $319,541 project grant for "Collaborative Research: Causal Structures: Experiments and Machine Learning." This 3-year research project aims to understand how economic agents develop subjective causal models and narratives to interpret information and make decisions. The researchers will conduct a series of experiments to...

This National Science Foundation (NSF) Division of Social and Economic Science Project Grant award of $234,489 supports collaborative research at New York University (NYU) from September 1, 2023 to August 31, 2026. The primary objectives are to: Conduct a series of experiments to understand how people form subjective causal models based on observed data patterns, and how these models may be influenced by preconceptions triggered by natural contexts. This will provide insights into how economic...